A global team of 20+ experts have compiled this list of 10 Best Probability & Statistics Courses, Classes, Tutorial, Certification and Training for 2019. It includes both paid and free learning resources available online to help you learn Probability and Statistics. These courses are suitable for beginners, intermediate learners as well as experts.

Demystify data in R, build analysis reports, learn Bayesian statistical inference and modeling in this program by Duke University. You will also learn to communicate statistical results, critique data-based claims, evaluate data based decisions and visualize data with R. Course is created and taught by Mine Çetinkaya-Rundel, Associate Professor of the Practice; David Banks, Professor of the Practice; Colin Rundel, Assistant Professor of the Practice and Merlise A Clyde, Professor. This is an ideal choice if you want to learn Probability and Statistics with R.

Review – Great, diversed material presented in a lively fashion. Inspiring and well explained. The supplementary coursebook with exercises gives the opportunity to study the subject deeper. A lot of real-life examples and a convenient way to practice using R. If the Statistics is for you, this will increase your motivation to study it.

This is a comprehensive course that covers all aspects of data science. The statistics part of this program will help you learn about Statistical inference, the process of drawing conclusions from data. It will cover all the broad theories (frequentists, Bayesian, likelihood) for performing inference. The program is created and taught by Roger D. Peng, PhD Associate Professor, Biostatistics; Brian Caffo, PhD Professor, Biostatistics and Jeff Leek, PhD Associate Professor, Biostatistics.

Review – I absolutely loved this course and felt like i learned a lot about statistics. This was very informative and the peer graded assignment was a perfect way to conclude the course, by having to perform all of the phases in Data Science that I learned by taking other courses in this series. Thank you for this course! Looking forward to the next set of courses.

Comprising of four online courses this MicroMasters program will guide you to gain the foundational knowledge required for understanding the methods and tools used in data science and get hands-on with machine learning and data analysis. Commence from the very basics of probability and statistics before moving on to data analysis techniques and machine learning algorithms. It is advisable to have college-level calculus, mathematical reasoning, and python programming proficiency to make the most of this certification. By the end of the program, you will be ready to apply to various data science profiles.

Key USPs-

– Strengthen your foundation of data science, statistics, and machine learning throughout the series of 5 courses.

– Instructors provide tips and advice on the best practices to develop and implement algorithms using the tools.

– Learn to analyze big data and make data-driven predictions through statistical inference and probabilistic modeling to extract meaningful data for decision making.

– Build machine learning algorithms to make sense of the unstructured data and gain relevant information.

– Work on popular unsupervised learning methods such as clustering methodologies and supervised methods such as deep neural networks.

– There are various job titles that can be applied to, after the completion of this certification such as data scientist, data analyst, system analyst to name a few.

Duration: 2 to 16 weeks per course, 10 to 14 hours per week, per course

In this specialization, you will learn to identify and ask interesting questions, analyze data sets and interpret results accurately to make solid evidence-based decisions. The lessons will talk about the research methods, design and statistical analysis for research questions based on social science. Along with this, the final project gives you the opportunity to apply the knowledge acquired in the classes to develop your own questions, gather data, analyze and report it using statistical methods. Upon the completion of the certification, you will have the confidence to take on more complex research questions and find the answers to them.

Key USPs-

– As this is a beginner level program so no specific prerequisite is required for enrollment.

– Discover the principles of scientific methods in the behavioral and social sciences.

Review – This course was excellent in all aspects, including the interesting and extensive material, as well as Dr. Annemarie Zand Scholten’s brilliant lectures that help students digest and enjoy the content.

This program is meant for all those who are interested in comprehending business data analysis tools and techniques. Learn about essential spreadsheet functions and understand how to do data modeling. It also includes basic probability concepts, Linear Regression Model among other key areas. You should have access to Microsoft Excel 2010 or later in order to complete this course. It is taught by Sharad Borle, Associate Professor of Management.

Review – Best Course to understand Linear Regression.Thank you team Rice University for simple yet effective course on Linear Regression.Do enroll for this course if you want to understand linear regression thoroughly.

This course introduces the Bayesian approach to statistics, starting with the concept of probability and moving to the analysis of data. It is an intermediate level specialization meant for students with basic knowledge about Statistics and will be taught by Herbert Lee, Professor Applied Mathematics and Statistics.

Review – Interesting, challenging, informative, entertaining, Herbie Lee is an excellent presenter of a very well prepared introduction to what seems to be a more rational and coherent approach to extracting, understanding and evaluating quantative information from data

The second course in the series builds on the first part and helps you go deeper in this domain. It includes more general models and computational techniques to fit them. You will be introduces to MCMC methods, programming language R and JAGS. The course is a heady mix of theoretical and practical knowledge and a project follows the curriculum bit to help you apply what you learn.

George Ingersoll is the Associate Dean of Executive MBA Programs at the UCLA Anderson School of Management. He has created this workshop, that will teach you probability, sampling, regression and decision analysis. This statistics tutorial is ideal for starters and people with intermediate level understanding.

Review – Now completed the course and think it is excellent. I’ve learned theory and application – best of all I’ve learned what is possible with these techniques. I can be a better businessman and investor using this knowledge. – Edward Strover

Kirill Eremenko is an expert trainer on Data Science! He has taught 400,000+ students so far and enjoys an average rating of 4.5 from his students! In this tutorial, he will teach you about the core stats required for a career in data science. He will help you master Statistical Significance, Confidence Intervals and a lot more.

Review – The course material was presented in an easy to understand method with many examples. Covered understanding and basic equations, but not so much math that the student gets lost. The graphics , equations, and some repetition really helped capture the concepts. The homework challenges gives a chance to practice the lesson material. External references and links were good for slightly different viewpoints and explanations . Overall a great job by the team. I’ve already signed up for more of Kirill’s courses. – Frederick Wheeler

This course will teach you how casual effects are defined, what assumptions about your data and models are necessary as well the techniques to implement and interpret some popular statistical methods. You will also have the opportunity to get hands-on and apply these methods to example data in R. Overall this program will show you the importance of the concepts covered in many different fields of study.

Key USPs-

– Define the casual effects using potential outcomes.

– Describe the difference between association and causation and express assumptions with casual graphs.

– Explore and implement several types of causal inference methods such as matching, instrumental variables, inverse probability of treatment weighting.

– Recognize the casual assumptions are necessary for each type of statistical method.

– The training is divided into appropriate sections and taught by experts with years of experience.

– Complete all the graded assessments, quizzes, and practical lessons to earn the course completion certificate.

Learn about descriptive & inferential statistics, hypothesis testing, Regression analysis and more in this training tailor made for statistics for business. Also learn how to plot different types of data, calculate the measures of central tendency, asymmetry and variability.

Review – The illustration is wonderful. The instructor explains the concept well. These concepts are quite complex but they are well-presented in a way that I can understand. All the exercises are great, they help me understand the concept even better. I wish that for the last section or the Assumption section there will be more exercises. I also wish that there is more explanation on the ANOVA table such as how you guys get those numbers, how to use them efficiently etc. – Huong N Le

So that was our take on best statistics and probability classes and tutorials online. Hope you found the one you were looking for. Do look around on our website to find more data science and related courses. You may be interested in checking out Best R Tutorial, Best Data Science Course, Best Python Tutorial in addition to Blockchain Course. Cheers and all the best! Team Digital Defynd!

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